Abstract

The international 1000 Genomes Project is designed to generate a new dataset of high resolution variation in the human genome to support various studies on human biology, including human population genetics, association studies and studies of human diseases. The genomes of more than 1000 anonymized individuals from 10 populations will be sequenced using state of the art sequencing technologies. This project is in response to a RFA (RFA-HG-09-002) for analyzing the dataset. It will focus on the area of estimating mutational parameter, characterizing linkage disequilibrium and detecting natural selection on various locations of the human genome. The primary aim is to develop new/or improve existing statistical methods based mostly on coalescent theory taking into consideration uniqueness of the large sample and unavoidable large uncertainties in the sequences. The newly developed or improved methods will be implemented in a user-friendly software package.

Public Health Relevance

Since one primary aim of the 1000 genomes project is to provide high resolution variation for studying human diseases, a proper understanding, such as through the research of this project, these data will be fundamental for their use for human biological studies, including medical research.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project--Cooperative Agreements (U01)
Project #
1U01HG005728-01
Application #
7883727
Study Section
Special Emphasis Panel (ZHG1-HGR-M (J1))
Program Officer
Brooks, Lisa
Project Start
2010-05-28
Project End
2012-04-30
Budget Start
2010-05-28
Budget End
2011-04-30
Support Year
1
Fiscal Year
2010
Total Cost
$407,335
Indirect Cost

  Institution

Name
University of Texas Health Science Center Houston
Department
Type
Other Domestic Higher Education
DUNS #
800771594
City
Houston
State
TX
Country
United States
Zip Code
77225

  Publications

1000 Genomes Project Consortium; Auton, Adam; Brooks, Lisa D et al. (2015) A global reference for human genetic variation. Nature 526:68-74
Liu, Xiaoming; Fu, Yun-Xin (2015) Exploring population size changes using SNP frequency spectra. Nat Genet 47:555-9
Xue, Cheng; Liu, Xiaoming; Gong, Yun et al. (2013) Significantly fewer protein functional changing variants for lipid metabolism in Africans than in Europeans. J Transl Med 11:67
Luo, Li; Zhu, Yun; Xiong, Momiao (2013) Smoothed functional principal component analysis for testing association of the entire allelic spectrum of genetic variation. Eur J Hum Genet 21:217-24
Shugart, Yin Yao; Zhu, Yun; Guo, Wei et al. (2012) Weighted pedigree-based statistics for testing the association of rare variants. BMC Genomics 13:667
1000 Genomes Project Consortium; Abecasis, Goncalo R; Auton, Adam et al. (2012) An integrated map of genetic variation from 1,092 human genomes. Nature 491:56-65
Luo, Li; Zhu, Yun; Xiong, Momiao (2012) A novel genome-information content-based statistic for genome-wide association analysis designed for next-generation sequencing data. J Comput Biol 19:731-44
Zhu, Yun; Xiong, Momiao (2012) Family-based association studies for next-generation sequencing. Am J Hum Genet 90:1028-45
Liu, Xiaoming (2012) jPopGen Suite: population genetic analysis of DNA polymorphism from nucleotide sequences with errors. Methods Ecol Evol 3:624-627
Siu, Hoicheong; Jin, Li; Xiong, Momiao (2012) Manifold learning for human population structure studies. PLoS One 7:e29901

Showing the most recent 10 out of 12 publications